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Image reconstruction from data collected over full-angular range (FAR) in dual-energy CT (DECT) is well-studied. There exists interest in DECT with advanced scan configurations in which data are collected only over limited-angular ranges (LARs) for meeting unique workflow needs in certain practical imaging applications, and thus in the algorithm development for image reconstruction from such LAR data. The objective of the work is to investigate and prototype image reconstructions in DECT with LAR scans. We investigate and prototype optimization programs with various designs of constraints on the directional-total-variations (DTVs) of virtual monochromatic images and/or basis images, and derive the DTV algorithms to numerically solve the optimization programs for achieving accurate image reconstruction from data collected in a slew of different LAR scans. Using simulated and real data acquired with low- and high-kV spectra over LARs, we conduct quantitative studies to demonstrate and evaluate the optimization programs and their DTV algorithms developed. As the results of the numerical studies reveal, while the DTV algorithms yield images of visual quality and quantitative accuracy comparable to that of the existing algorithms from FAR data, the former reconstruct images with improved visualization, reduced artifacts, and also enhanced quantitative accuracy when applied to LAR data in DECT. Optimization-based, one-step algorithms, including the DTV algorithms demonstrated, can be developed for quantitative image reconstruction from spectral data collected over LARs of extents that are considerably smaller than the FAR in DECT. The theoretical and numerical results obtained can be exploited for prototyping designs of optimization-based reconstructions and LAR scans in DECT, and they may also yield insights into the development of reconstruction procedures in practical DECT applications. The approach and algorithms developed can naturally be applied to investigating image reconstruction from LAR data in multi-spectral and photon-counting CT.
Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. (Copyright © 2023 Elsevier B.V. All rights reserved.)
Acetyl Coenzyme A metabolism, Cell Extracts, Escherichia coli metabolism, Saccharomyces cerevisiae genetics, Saccharomyces cerevisiae metabolism, and Metabolic Engineering
Building and optimizing biosynthetic pathways in engineered cells holds promise to address societal needs in energy, materials, and medicine, but it is often time-consuming. Cell-free synthetic biology has emerged as a powerful tool to accelerate design-build-test-learn cycles for pathway engineering with increased tolerance to toxic compounds. However, most cell-free pathway prototyping to date has been performed in extracts from wildtype cells which often do not have sufficient flux towards the pathways of interest, which can be enhanced by engineering. Here, to address this gap, we create a set of engineered Escherichia coli and Saccharomyces cerevisiae strains rewired via CRISPR-dCas9 to achieve high-flux toward key metabolic precursors; namely, acetyl-CoA, shikimate, triose-phosphate, oxaloacetate, α-ketoglutarate, and glucose-6-phosphate. Cell-free extracts generated from these strains are used for targeted enzyme screening in vitro. As model systems, we assess in vivo and in vitro production of triacetic acid lactone from acetyl-CoA and muconic acid from the shikimate pathway. The need for these platforms is exemplified by the fact that muconic acid cannot be detected in wildtype extracts provided with the same biosynthetic enzymes. We also perform metabolomic comparison to understand biochemical differences between the cellular and cell-free muconic acid synthesis systems (E. coli and S. cerevisiae cells and cell extracts with and without metabolic rewiring). While any given pathway has different interfaces with metabolism, we anticipate that this set of pre-optimized, flux enhanced cell extracts will enable prototyping efforts for new biosynthetic pathways and the discovery of biochemical functions of enzymes.
(Copyright © 2023 International Metabolic Engineering Society. Published by Elsevier Inc. All rights reserved.)
Nanotechnology, Microfluidics, Bioreactors, Microfluidic Analytical Techniques, and Nanopores
While injection molding is becoming the fabrication modality of choice for high-scale production of microfluidic devices, especially those used for in vitro diagnostics, its translation into the growing area of nanofluidics (structures with at least one dimension <100 nm) has not been well established. Another prevailing issue with injection molding is the high startup costs and the relatively long time between device iterations making it in many cases impractical for device prototyping. We report, for the first time, functional nanofluidic devices with dimensions of critical structures below 30 nm fabricated by injection molding for the manipulation, identification, and detection of single molecules. UV-resin molds replicated from Si masters served as mold inserts, negating the need for generating Ni-mold inserts via electroplating. Using assembled devices with a cover plate via hybrid thermal fusion bonding, we demonstrated two functional thermoplastic nanofluidic devices. The first device consisted of dual in-plane nanopores placed at either end of a nanochannel and was used to detect and identify single ribonucleotide monophosphate molecules via resistive pulse sensing and obtain the effective mobility of the molecule through nanoscale electrophoresis to allow its identification. The second device demonstrated selective binding of a single RNA molecule to a solid phase bioreactor decorated with a processive exoribonuclease, XRN1. Our results provide a simple path towards the use of injection molding for device prototyping in the development stage of any nanofluidic or even microfluidic application, through which rapid scale-up is made possible by transitioning from prototyping to high throughput production using conventional Ni mold inserts.
Neural networks attract significant attention in almost every field due to their widespread applications in various tasks. However, developers often struggle with debugging due to the black-box nature of neural networks. Visual analytics provides an intuitive way for developers to understand the hidden states and underlying complex transformations in neural networks. Existing visual analytics tools for neural networks have been demonstrated to be effective in providing useful hints for debugging certain network architectures. However, these approaches are often architecture-specific with strong assumptions of how the network should be understood. This limits their use when the network architecture or the exploration goal changes. In this paper, we present a general model and a programming toolkit, Neural Network Visualization Builder (NNVisBuilder), for prototyping visual analytics systems to understand neural networks. NNVisBuilder covers the common data transformation and interaction model involved in existing tools for exploring neural networks. It enables developers to customize a visual analytics interface for answering their specific questions about networks. NNVisBuilder is compatible with PyTorch so that developers can integrate the visualization code into their learning code seamlessly. We demonstrate the applicability by reproducing several existing visual analytics systems for networks with NNVisBuilder. The source code and some example cases can be found at https://github.com/sysuvis/NVB.
The flapping-wing technology has emerged recently in the application of unmanned aerial robotics for autonomous flight, control, inspection, monitoring, and manipulation. Despite the advances in applications and outdoor manual flights (open-loop control), closed-loop control is yet to be investigated. This work presents a nonlinear optimal closed-loop control design via the state-dependent Riccati equation (SDRE) for a flapping-wing flying robot (FWFR). Considering that the dynamic modeling of the flapping-wing robot is complex, a proper model for the implementation of nonlinear control methods is demanded. This work proposes an alternative approach to deliver an equivalent dynamic for the translation of the system and a simplified model for orientation, to find equivalent dynamics for the whole system. The objective is to see the effect of flapping (periodic oscillation) on behavior through a simple model in simulation. Then the SDRE controller is applied to the derived model and implemented in simulations and experiments. The robot bird is a 1.6 m wingspan flapping-wing system (six-degree-of-freedom robot) with four actuators, three in the tail, and one as the flapping input. The underactuated system has been controlled successfully in position and orientation. The control loop is closed by the motion capture system in the indoor test bed where the experiments of flight have been successfully done.
Competing Interests: Declaration of competing interest The authors declare that there is no conflict of interest for this paper. (Copyright © 2023 The Author(s). Published by Elsevier Ltd.. All rights reserved.)
Premature birth and neonatal mortality are significant global health challenges, with 15 million premature births annually and an estimated 2.5 million neonatal deaths. Approximately 90% of preterm births occur in low/middle income countries, particularly within the global regions of sub-Saharan Africa and South Asia. Neonatal hypothermia is a common and significant cause of morbidity and mortality among premature and low birth weight infants, particularly in low/middle-income countries where rates of premature delivery are high, and access to health workers, medical commodities, and other resources is limited. Kangaroo Mother Care/Skin-to-Skin care has been shown to significantly reduce the incidence of neonatal hypothermia and improve survival rates among premature infants, but there are significant barriers to its implementation, especially in low/middle-income countries (LMICs). The paper proposes the use of a multidisciplinary approach to develop an integrated mHealth solution to overcome the barriers and challenges to the implementation of Kangaroo Mother Care/Skin-to-skin care (KMC/STS) in LMICs. The innovation is an integrated mHealth platform that features a wearable biomedical device (NeoWarm) and an Android-based mobile application (NeoRoo) with customized user interfaces that are targeted specifically to parents/family stakeholders and healthcare providers, respectively. This publication describes the iterative, human-centered design and participatory development of a high-fidelity prototype of the NeoRoo mobile application. The aim of this study was to design and develop an initial ("A") version of the Android-based NeoRoo mobile app specifically to support the use case of KMC/STS in health facilities in Kenya. Key functions and features are highlighted. The proposed solution leverages the promise of digital health to overcome identified barriers and challenges to the implementation of KMC/STS in LMICs and aims to equip parents and healthcare providers of prematurely born infants with the tools and resources needed to improve the care provided to premature and low birthweight babies. It is hoped that, when implemented and scaled as part of a thoughtful, strategic, cross-disciplinary approach to reduction of global rates of neonatal mortality, NeoRoo will prove to be a useful tool within the toolkit of parents, health workers, and program implementors.
Competing Interests: I have read the journal’s policy and the authors of this manuscript have the following competing interests: Dr. Sherri Bucher has been awarded intellectual property protection for invention of the NeoWarm biomedical device. This includes US patent US10390630B2, Nigeria NG/PT/C/2018/2802 and ARIPO patent PT/C/2018/2802. The authors declare no other potential conflicts of interest with respect to research, authorship, financial relationships, and/or publication of the article. (Copyright: © 2023 Bucher et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)
The layup process of large composite structures made from dry reinforcement fabrics is considered. One such structure is a wind turbine blade, for which the current draping process is mostly manual. Automating the draping process will, therefore, lower the costs. Based on a literature review, a new concept is synthesized and analyzed using an advanced finite element model with rigid multi-body kinematics and a dedicated material model for the fabric. The material model is calibrated using experimental coupon tests, i.e. the bias-extension test (shear) and Peirce's cantilever test (out-of-plane bending). The concept is analyzed numerically by means of a simple parameter study and draping test cases on a flat mold as well as a general double-curved mold. The simulation results show that the concept is feasible for the draping operation and is thus qualified for the subsequent physical prototyping.
Competing Interests: The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Johnny Jakobsen reports financial support was provided by 10.13039/501100022591The Energy Technology Development and Demonstration Programme, Grant no. 64019-0514. Christian Krogh reports financial support was provided by 10.13039/501100022591The Energy Technology Development and Demonstration Programme, Grant no. 64019-0514. (© 2023 The Authors.)
Photolithography is the foundational process at the root of micro-electromechanical (MEMS) and microfluidic systems manufacture. The process is descendant from the semiconductor industry, originating from printed circuit board and microprocessor fabrication, itself historically performed in a cleanroom environment utilizing expensive, specialist microfabrication equipment. Consequently, these conditions prove cost-prohibitive and pose a large barrier to entry. We present a novel homebrew, "do-it-yourself" method for performing photolithography to produce master mold wafers using only household appliances and homemade equipment at the bench side, outside of a cleanroom, producing a range of designs including spiral, serpentine, rectangular, and circulatory. Our homebrew processes result in the production of microfluidic channels with feature resolution of ∼85 μm width and 50 μm height utilizing inkjet-printed photomasks on transparency film to expose dry-film photoresist. From start to finish, the entire process takes under <90 min and costs <£300. With SU8 epoxy negative photoresist and a chrome photomask, our low-cost UV exposure apparatus and homemade spincoater could be used to produce PDMS devices containing large arrays of identical microwells measuring 4.4 μm in diameter. We show that our homebrew method produces both rectangular and spiral microfluidic channels with better results than can be achieved by SLA 3D printing by comparison, and amenable to bonding into multilayer functional microfluidic devices. As these methods are fundamental to microfluidics manufacture, we envision that this work will be of value to researchers across a broad range of disciplines, such as those working in resource-constrained countries or conditions, with many and widely varying applications.
Competing Interests: The authors declare no competing financial interest. (© 2023 The Authors. Published by American Chemical Society.)
Models of urea kinetics facilitate a mechanistic understanding of urea transfer and provide a tool for optimizing dialysis efficacy. Dual-compartment models have largely replaced single-compartment models as they are able to accommodate the urea rebound on the cessation of dialysis. Modeling the kinetics of urea and other molecular species is frequently regarded as a rarefied academic exercise with little relevance at the bedside. We demonstrate the utility of System Dynamics in creating multi-compartment models of urea kinetics by developing a dual-compartment model that is efficient, intuitive, and widely accessible to a range of practitioners. Notwithstanding its simplicity, we show that the System Dynamics model compares favorably with the performance of a more complex volume-average model in terms of calibration to clinical data and parameter estimation. Its intuitive nature, ease of development/modification, and excellent performance with real-world data may make System Dynamics an invaluable tool in widening the accessibility of hemodialysis modeling.
(© 2023. The Author(s).)
Optical sensing offers several advantages owing to its non-invasiveness and high sensitivity. The miniaturization of optical sensors will mitigate spatial and weight constraints, expanding their applications and extending the principal advantages of optical sensing to different fields, such as healthcare, Internet of Things, artificial intelligence, and other aspects of society. In this study, we present the development of a miniature optical sensor for monitoring thrombi in extracorporeal membrane oxygenation (ECMO). The sensor, based on a complementary metal-oxide semiconductor integrated circuit (CMOS-IC), also serves as a photodiode, amplifier, and light-emitting diode (LED)-mounting substrate. It is sized 3.8 × 4.8 × 0.75 mm 3 and provides reflectance spectroscopy at three wavelengths. Based on semiconductor and microelectromechanical system (MEMS) processes, the design of the sensor achieves ultra-compact millimeter size, customizability, prototyping, and scalability for mass production, facilitating the development of miniature optical sensors for a variety of applications.
Since temperature and its spatial, and temporal variations affect a wide range of physical properties of material systems, they can be used to create reconfigurable spatial structures of various types in physical and biological objects. This paper presents an experimental optical setup for creating tunable two-dimensional temperature patterns on a micrometer scale. As an example of its practical application, we have produced temperature-induced magnetization landscapes in ferrimagnetic yttrium iron garnet films and investigated them using micro-focused Brillouin light scattering spectroscopy. It is shown that, due to the temperature dependence of the magnon spectrum, spatial temperature distributions can be visualized even for microscale thermal patterns.
(© 2023 Author(s). All article content, except where otherwise noted, is licensed under a Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).)
Animals, Antivenins therapeutic use, Antibodies, Monoclonal therapeutic use, Snake Bites diagnosis, Snake Bites drug therapy, Crotalid Venoms therapeutic use, and Bothrops
Background: Brazil is home to a multitude of venomous snakes; perhaps the most medically relevant of which belong to the Bothrops genus. Bothrops spp. are responsible for roughly 70% of all snakebites in Brazil, and envenomings caused by their bites can be treated with three types of antivenom: bothropic antivenom, bothro-lachetic antivenom, and bothro-crotalic antivenom. The choice to administer antivenom depends on the severity of the envenoming, while the choice of antivenom depends on availability and on how certain the treating physician is that the patient was bitten by a bothropic snake. The diagnosis of a bothropic envenoming can be made based on expert identification of the dead snake or a photo thereof or based on a syndromic approach wherein the clinician examines the patient for characteristic manifestations of envenoming. This approach can be very effective but requires staff that has been trained in clinical snakebite management, which, unfortunately, far from all relevant staff has.
Results: In this article, we describe a prototype of the first lateral flow assay (LFA) capable of detecting venoms from Brazilian Bothrops spp. The monoclonal antibodies for the assay were generated using hybridoma technology and screened in sandwich enzyme-linked immunosorbent assays (ELISAs) to identify Bothrops spp.-specific antibody sandwich pairs. The prototype LFA is able to detect venom from several Bothrops spp. The LFA has a limit of detection (LoD) of 9.5 ng/mL in urine, when read with a commercial reader, and a visual LoD of approximately 25 ng/mL. Significance: The work presented here serves as a proof of concept for a genus-specific venom detection kit that could support physicians in diagnosing Bothrops envenomings. Although further optimisation and testing is needed before the LFA can find clinical use, such a device could aid in decentralising antivenoms in the Brazilian Amazon and help ensure optimal snakebite management for even more victims of this highly neglected disease. Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Cecilie Knudsen, Jonas A. Jürgensen, Søren H. Dam, Aleksander M. Haack, Rasmus U. W. Friis, and Andreas H. Laustsen are co-founders of VenomAid Diagnostics A/S. Jonas A. Jürgensen, Pelle D. Knudsen, and Georgina M. Ross are employed by VenomAid Diagnostics A/S. Cecilie Knudsen is an industrial PhD student at the Technical University of Denmark. Her PhD is co-sponsored by Innovation Fund Denmark and BioPorto Diagnostics A/S. Cecilie Knudsen, Jonas A. Jürgensen, Søren H. Dam, Aleksander M. Haack, Rasmus U. W. Friis, and Andreas H. Laustsen have been designated as inventors on a patent application related to the work presented here. (Copyright © 2023 The Author(s). Published by Elsevier B.V. All rights reserved.)
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